This　paper　explores　the　application　of　multidisciplinary　design　optimization　to　the　blades　in　horizontal-axis　wind　turbines.　The　aerodynamics　and　structural　performance　of　blades　are　considered　in　the　optimization　framework.　In　the　aerodynamic　discipline,　class　function/shape　function　transformation-based　parameterized　modeling　is　used　to　express　the　airfoil.　The　Wilson　method　is　employed　to　obtain　the　aerodynamic　shape　of　the　blade.　Computational　fluid　dynamics　numerical　simulation　is　performed　to　analyze　the　aerodynamics　of　the　blade.　In　the　structural　discipline,　the　materials　and　ply　lay-up　design　are　studied.　Finite　element　method-based　modal　analysis　and　static　structural　analysis　are　conducted　to　verify　the　structural　design　of　the　blade.　A　collaborative　optimization　framework　is　set　up　on　the　Isight　platform,　employing　a　genetic　algorithm　to　find　the　optimal　solution　for　the　blade＇s　aerodynamics　and　structural　properties.　In　the　optimization　framework,　the　design　variables　refer　to　the　length　of　the　blade　chord,　twist　angle,　and　lay-up　thickness.　Additionally,　Kriging　surrogate　models　are　constructed　to　reduce　the　numerical　simulation　time　required　during　optimization.　An　optimal　Latin　hypercube　sampling　method-based　experimental　design　is　employed　to　determine　the　samples　used　in　the　surrogate　models.　The　optimized　blade　exhibits　improved　performance　in　both　the　aerodynamic　and　the　structural　disciplines.